GitHub issues allow you to post questions, report bugs, seek advice, and all manner of consulting other human beings about the course, R, and related tooling.
Caution: Do not submit code which may contain solutions to the lab assignments.
Pro Tip: Check both "Open" and "Closed" issues for your issue before creating a new one.
Assigning Issues & Tagging GitHub Users
Assigning Contributors: You can assign an issue to a specific contributor to the course "repository" or "repo" in a new or existing issue by selecting "Assignees" in the upper right navigation bar of an issue's post thread. It looks like this:
Doing so will alert that contributor to your message but typically indicates that you expect her or him to help fix it.
Tagging Users: If you just want to tag a user, simply type @ and her or his username in any post. For example: @jamisoncrawford.
Pro Tip: Exhaust every troubleshooting option available before consulting a human!
Labeling Issues
Labeling issues is critical for categorizing them, helping others find them, and in general "tagging" an issue with an identifier that helps users understand what your issue concerns.
In any new or existing issues, select "Labels" in the upper right navigation bar of an issue's post thread. It looks like this:
There are tags for labs, reading assignments, R code, Markdown, and Github, as well as for reporting bugs in the course site. We may add more if necessary.
Pro Tip: Use more than one tag to help users more easily understand your issue!
Important Information to Include in Any Issue
Always submit issues that contain the details necessary for you to receive the right help:
Use a descriptive title, like naming a specific lab assignment, question, or R function
Use one or more tags to help users understand your dilemma
Concerning coding issues:
Always include a description of your expectation and the unexpected behavior
Include any error or warning messages printed as a result of your code
Include any packages (i.e. extensions) on which your code depends
Include the code itself using "fences", or "backticks" - it looks like:
...and it formats like so:
x <- data.frame(mtcars)
summary(x)
If reproducing your code gives away a lab solution, use a sample dataset or different functions.
What are "Issues"?
GitHub issues allow you to post questions, report bugs, seek advice, and all manner of consulting other human beings about the course, R, and related tooling.
Caution: Do not submit code which may contain solutions to the lab assignments.
Pro Tip: Check both "Open" and "Closed" issues for your issue before creating a new one.
Assigning Issues & Tagging GitHub Users
Assigning Contributors: You can assign an issue to a specific contributor to the course "repository" or "repo" in a new or existing issue by selecting "Assignees" in the upper right navigation bar of an issue's post thread. It looks like this:
Doing so will alert that contributor to your message but typically indicates that you expect her or him to help fix it.
Tagging Users: If you just want to tag a user, simply type
@and her or his username in any post. For example: @jamisoncrawford.Pro Tip: Exhaust every troubleshooting option available before consulting a human!
Labeling Issues
Labeling issues is critical for categorizing them, helping others find them, and in general "tagging" an issue with an identifier that helps users understand what your issue concerns.
In any new or existing issues, select "Labels" in the upper right navigation bar of an issue's post thread. It looks like this:
There are tags for labs, reading assignments, R code, Markdown, and Github, as well as for reporting bugs in the course site. We may add more if necessary.
Pro Tip: Use more than one tag to help users more easily understand your issue!
Important Information to Include in Any Issue
Always submit issues that contain the details necessary for you to receive the right help:
Concerning coding issues:
errororwarningmessages printed as a result of your code...and it formats like so:
If reproducing your code gives away a lab solution, use a sample dataset or different functions.